What are the responsibilities and job description for the Senior Robotic AI-Perception Engineer - Only W2 position at Saransh Inc?
Role: Senior Robotic AI-Perception Engineer
Location: Warren, MI (Onsite from Day 1)
Job Type: W2 Contract
Main Skills: Senior Robotic AI-Perception Engineer (AI/ML, perception, computer vision, Python, TensorFlow and/or PyTorch)
Key Responsibilities
Location: Warren, MI (Onsite from Day 1)
Job Type: W2 Contract
Main Skills: Senior Robotic AI-Perception Engineer (AI/ML, perception, computer vision, Python, TensorFlow and/or PyTorch)
Key Responsibilities
- Design, develop, and implement perception algorithms for segmentation, scene understanding, object detection and localization, classification, and dynamic tracking.
- Integrate AI and computer vision algorithms with ROS (Robot Operating System) for real-time deployment on autonomous robots (e.g., mobile manipulators).
- Design and maintain cloud-based pipelines for data collection, annotation, preprocessing, model training, and evaluation.
- Collaborate with hardware engineers, software engineers, and domain experts to integrate with mapping, motion planning, and controls.
- Develop offline tools to test and validate perception models in both simulation and real-world environments.
- Stay updated with emerging technologies and best practices in robotic perception; lead and participate in academic and industrial collaborations.
- Generate intellectual property, document results, and publish papers.
- Passion for robotics and a strong desire to accelerate the application of robotics with AI.
- Master’s or Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field (or Bachelor’s degree with exceptional track record).
- 3 years of experience developing and deploying AI/ML, perception, and computer vision (e.g., mono and stereo cameras, RGB-D, event camera, LiDAR) on robotic systems.
- Proficiency in Python or C with hands-on experience in deep learning frameworks such as TensorFlow and PyTorch.
- Solid understanding of robotics fundamentals, perception and navigation methods (e.g., SLAM, planning), and their typical strengths and shortcomings.
- Consistently seeks opportunities and embraces challenges to drive self-growth and improvement.
- Ph.D. in Computer Science, Machine Learning, Robotics, Computer Vision, or a related research field.
- Hands-on robotics experience, such as autonomous vehicles (AV), ADAS, or industrial automation systems in manufacturing environments.
- Experience with robotics frameworks such as ROS/ROS2 (e.g., Nav2, MoveIt).
- Understanding of CI/CD pipelines and modern software development practices.